Proceedings of the 1st Iberic Conference on Theoretical and Experimental Mechanics and Materials /

11th National Congress on Experimental Mechanics. Porto/Portugal 4-7 November 2018.

Ed. J.F. Silva Gomes. INEGI/FEUP (2018); ISBN: 978-989-20-8771-9; pp. 739-744.

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PAPER REF: 7375

BIM-BASED ROBOTIC WELDING SYSTEM CAPABLE OF DEALING

WITH SMALL BATCHES OF STRUCTURAL STEEL ASSEMBLIES

Vítor Ferreira1(*)

, Paulo J. Morais1, Helena Gouveia

1, Margarida Pinto

1, Luís Rocha

2, Germano Veiga

2,

Pedro Malaca3, José Oliveira

3, José Pinto

4, José Melo

4, Nuno Oliveira

4

1ISQ - Instituto de Soldadura e Qualidade, Av. Prof. Dr. Cavaco Silva 33, 2740-120 Porto Salvo, Portugal 2INESC-TEC, R. Dr. Roberto Frias, 4200-465 Porto, Portugal 3Sarkkis Robotics, Rua Alfredo Allen 461, 4200-135 Porto, Portugal 4Norfersteel, R. Comendador Arlindo Soares de Pinho 1910, 3730-901 Vale de Cambra, Portugal (*)

Email: vmferreira@isq.pt

ABSTRACT

The CoopWeld project combined robots, sensors and automatic offline programming to

successfully achieve a robotic welding system capable of dealing with frequent small batches

and one-off productions in the fabrication of structural steel assemblies, while minimizing

input from robotic cell operators.

Keywords: BIM, robotic welding, offline programming, projection mapping, sensors, seam

finding, seam tracking.

INTRODUCTION

The vast majority of traditional robotic welding applications, such as found in the automotive

industry for either arc or spot welding, rely heavily on the use of welding jigs and fixtures for

the repetitive and accurate positioning of parts and joints. Therefore, they do not require

sensing devices to locate joints or perform seam tracking. Thanks to large batch productions

of identical items, they allow for economically viable online and offline programming.

More recently, the right combination of robots, sensors and automatic offline programming

has begun to prove itself to be effective in dealing with production factors that traditionally

prevented the use of robots for welding small-batch structural assemblies. However, most

well-proven systems are conceptually sophisticated, expensive and aimed at high-level end-

users such as large and state-of-the-art shipyards.

The CoopWeld project succeeded in developing a low-cost robotic welding system capable of

dealing with frequent small batches and one-off productions through automatic offline

programming, minimizing input from robotic cell operators. The robotic system is aimed at

SMEs and limited to well-characterized and standardized non-generic product families. More

specifically, the system has been designed for the prefabrication of welded steel assemblies

such as pillars, roof beams and end frame beams used in the construction of industrial steel

buildings and warehouses (Figure 1).

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Fig. 1 - Typical assemblies welded in the CoopWeld robotic cell.

DESCRIPTION

Robot path generation is done through automatic offline programming using assembly models

produced in a BIM-enabled 3D CAD software (e.g. Tekla Structures). Besides providing an

accurate virtual geometry and virtual collision detection, these information-rich models

contain process-specific information needed to support fabrication, such as welding-related

data (Figure 2).

Fig. 2 - The CoopWeld robotic cell features a gantry-mounted welding robot on a long linear track

and a flipper beam rotator.

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Unlike some costly high-end systems, CoopWeld relies on collaborative interaction with

human operators for the fit-up of the steel assemblies to be welded as well as for validating

the proposed welding sequence and parameters. An intuitive human-machine interface (HMI)

is an essential feature of the CoopWeld robotic cell, allowing operators to validate

automatically generated robot paths (Figure 3).

Fig. 3 - Human-machine interface displaying robot path generation for a structural steel assembly.

A decision support system for setting all relevant welding process parameters is fully

integrated with the main HMI, allowing to deal with the different weld joint configurations

and preparation details that are typically found in actual fabrication. MAG (Metal Active Gas)

welding is the natural and obvious choice regarding welding process technology to be

employed in robotic welding of structural steel assemblies. Therefore, suitable values for

parameters such as wire feed speed, welding speed and possibly also torch oscillation must be

automatically generated for each and every joint, as dictated by design specifications, material

thickness and welding position (Figure 4).

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Fig. 4 - Welding parameters are automatically generated by a dedicated tool integrated with the

main human-machine interface.

Projection mapping using a laser mounted on the robot gantry frame assists the positioning

and tack welding operations that must be performed manually by a welder during fit-up, prior

to the robotic welding. Laser-generated lines and contour shapes are projected on the surfaces

of the main structural section, providing a valuable visual aid for the location of all the

different parts that should be manually tack welded onto the section. Projection mapping not

only saves a great deal of time during fit-up, it also provides a means to increase general

accuracy and process reliability (Figure 5).

Fig. 5 - Projection mapping system at work, showing the location of a stiffener on the main

structural section.

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Advanced sensors are integrated with design data to adaptively handle geometric variations.

Laser-based sensing is used to calibrate the cell for each new steel assembly and also to

perform joint location prior to welding. During the welding itself, through-the-arc seam

tracking (TAST) further compensates for part misplacement and warping (Figures 6 and 7).

Fig. 6 - The laser-based seam finding system uses 3D search routines to acquire the actual positioning of

manually tack welded parts, ensuring the weld beads are precisely deposited in the joints during robotic

final welding.

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Fig. 7 - Weld joint details of a stiffener welded to the main section.

CONCLUSION

While introducing robotics in production environments that traditionally rely on manual

welding, the cost-wise CoopWeld cell addresses the budget limitations often found in SMEs

concerned with fabrication and erection of structural steel.

The overall concept applies to a variety of well-characterized and standardized steel product

families, such as beams and columns for building structures, casings for medium- and high-

voltage transformers, small assemblies for shipbuilding, etc.

ACKNOWLEDGMENTS